Léo Saci

Value learning from trajectory optimization and Sobolev descent: A step toward reinforcement learning with superlinear convergence properties

The recent successes in deep reinforcement learning largely rely on the capabilities of generating masses of data, which in turn implies the use of a simulator. In particular, current progress in multi body dynamic simulators are under-pinning the implementation of reinforcement learning for end-to-…